5.4 Indirect Calculation of Fluxes: Bulk Formulas
The use of gust-probes is very expensive, and radiometers must be carefully maintained. Neither can be used to obtain long-term, global values of fluxes. To calculate these fluxes from practical measurements, we use observed correlations between fluxes and variables that can be measured globally.
For fluxes of sensible and latent heat and momentum, the correlations are called bulk formulas. They are:
Air temperature Ta is measured using thermometers on ships. It cannot be measured from space using satellite instruments. ts is measured using thermometers on ships or from space using infrared radiometers such as the AVHRR.
The specific humidity of air at 10 m above the sea surface qa is calculated from measurements of relative humidity made from ships. Gill (1982: pp: 39-41, 43-44, & 605-607) describes equations relating water vapor pressure, vapor density, and specific heat capacity of wet air. The specific humidity at the sea surface qs is calculated from ts assuming the air at the surface is saturated with water vapor. U10 is measured or calculated using the instruments or techniques described in Chapter 4. Note that wind stress is a vector with magnitude and direction. It is parallel to the surface in the direction of the wind.
The problem now becomes: How to calculate the fluxes across the sea surface required for studies of ocean dynamics? The fluxes include:
Furthermore, the fluxes must be accurate. We need an accuracy of approximately ± 15 W/m2. This is equivalent to the flux of heat which would warm or cool a column of water 100 m deep by roughly 1°C in one year. Table 5.2 lists typical accuracies of fluxes measured globally from space. Now, let s look at each variable.
Wind Speed and Stress Stress is calculated from wind observations made from ships at sea and from scatterometers in space as described in the last chapter.
Insolation is calculated from cloud observations made from ships and from visible-light radiometers on meteorological satellites. Satellite measurements are far more accurate than the ship data because it's very hard to measure cloudiness from below the clouds. Satellite measurements processed by the International Satellite Cloud Climatology Project ISCCP are the basis for maps of insolation and its variability from month to month (Darnell et al., 1988; Rossow and Schiffer 1991).
The basic idea behind the calculation of insolation is very simple. Sunlight at the top of the atmosphere is accurately known from the solar constant, latitude, longitude, and time. Sunlight is either reflected back to space by clouds, or it eventually reaches the sea surface. Only a small and nearly constant fraction is absorbed in the atmosphere. But, recent work by Cess et al., (1995) and Ramanathan et al., (1995) suggest that the simple idea may be incomplete, and that atmospheric absorption may be a function of cloudiness. Assuming atmospheric absorption is constant, insolation is calculated from:
Insolation = S (1 - A) - C
where S = 1365 W/m2 is the solar constant, A is albedo, the ratio of incident to reflected sunlight, and C is a constant which includes absorption by ozone and other atmospheric gases and by cloud droplets. Insolation is calculated from cloud data (which also includes reflection from aerosols) collected from instruments such as the AVHRR on meteorological satellites. Ozone and gas absorption are calculated from from known distributions of the gases in the atmosphere. QSW is calculated from satellite data with an accuracy of 5-7%.
Water Flux (Rainfall)
The most accurate measurements of rain rate in the tropics (±35°) are calculated from microwave radiometers and radar observations of rain at several frequencies using instruments on the Tropical Rain Measuring Mission TRMM launched in 1997. Rain for other times and latitudes can be calculated accurately by combining microwave data with infrared observations of the height of cloud tops and with rain gauge data (Figure 5.5). Rain is also calculated from the reanalysis of the output from numerical weather forecast models (Schubert, Rood, and Pfaendtner, 1993), and by combining ship and satellite observations with output from numerical weather-prediction models (Xie and Arkin, 1997).
The largest source of error is due to conversion of rain rate to cumulative rainfall, a sampling error. Rain is very rare, it is log-normally distributed, and most rain comes from a few storms. Satellites tend to miss storms, and data must be averaged over areas up to 5° on a side to obtain useful values of rainfall.
Net Long-Wave Radiation
Water Flux Out (Latent Heat Flux)
Sensible Heat Flux
|Department of Oceanography, Texas A&M University
Robert H. Stewart, firstname.lastname@example.org
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Updated on September 8, 2006